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skills/fine-tune/prompt_principles.md

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+# Prompt Optimization Principles
+
+Fundamental principles for designing prompts in LangGraph nodes.
+
+## 🎯 Prompt Optimization Principles
+
+### 1. Clarity
+
+**Bad Example**:
+```python
+SystemMessage(content="Analyze the input.")
+```
+
+**Good Example**:
+```python
+SystemMessage(content="""You are an intent classifier for customer support.
+
+Task: Classify user input into one of these categories:
+- product_inquiry: Questions about products or services
+- technical_support: Technical issues or troubleshooting
+- billing: Payment or billing questions
+- general: General questions or greetings
+
+Output only the category name.""")
+```
+
+**Improvements**:
+- ✅ Clearly defined role
+- ✅ Specific task description
+- ✅ Enumerated categories
+- ✅ Specified output format
+
+### 2. Structure
+
+**Bad Example**:
+```python
+prompt = f"Answer this: {question}"
+```
+
+**Good Example**:
+```python
+prompt = f"""Context:
+{context}
+
+Question:
+{question}
+
+Instructions:
+1. Base your answer on the provided context
+2. Be concise (2-3 sentences maximum)
+3. If the answer is not in the context, say "I don't have enough information"
+
+Answer:"""
+```
+
+**Improvements**:
+- ✅ Sectioned (Context, Question, Instructions, Answer)
+- ✅ Sequential instructions
+- ✅ Clear separators
+
+### 3. Specificity
+
+**Bad Example**:
+```python
+"Be helpful and friendly."
+```
+
+**Good Example**:
+```python
+"""Tone and Style:
+- Use a warm, professional tone
+- Address the customer by name if available
+- Acknowledge their concern explicitly
+- Provide actionable next steps
+
+Example:
+"Hi Sarah, I understand your concern about the billing charge. Let me review your account and get back to you within 24 hours with a detailed explanation."
+"""
+```
+
+**Improvements**:
+- ✅ Specific guidelines
+- ✅ Concrete examples provided
+- ✅ Measurable criteria